AI Platform Engineer : Full Time

We’re hiring for an AI Platform Engineers for a fulltime role with our client, Based in Mission District- San Francisco, California,

Please review the job description below and share your interest along with your most updated resume.

Role: AI Platform Engineers

Location : Mission District- San Francisco, California

Full-Time Position

Job Responsibilities :

We’re looking for AI Platform Engineers to build the foundations of our engineering stack - from AI productivity and deployment to monitoring, security, and cost optimization. This is one of the highest-impact and highest-responsibility roles in the company. Your work will increase the productivity of every team and shape how we build going forward.

What you'll do:

Build internal platforms and AI loops that increase company iteration speed

Strengthen security, compliance, and operational readiness

Improve CI/CD, testing, deployments, and developer environments

Evaluate and implement new tooling, storage, and compute systems

Enable non-technical staff to build and ship improvements safely

Enable technical teams to ship scalable, enterprise-ready systems faster

Resolve incidents and production fires with both immediate fixes and long-term solutions

Technical Stack needed

TypeScript and Python are primary languages; experience with web stack and Chrome extensions beneficial.

Focus on enabling AI tools and infrastructure for rapid development.

Seniority

5+ years of experience in platform engineering.

Work experience

Has shipped and maintained production platform infrastructure in a B2B SaaS environment -CI/CD, Kubernetes, containerization, cloud deployments, database migrations; has made painful mistakes and learned from them

Startup experience post-Series A; ideally has seen a company grow from Series A-B

You’re a great fit if you have:

Built and scaled complex infrastructure systems

Worked with Kubernetes, ETL pipelines, AWS/GCP/Cloudflare, CI/CD, and SOC 2 environments

Strong judgment across security, reliability, cost, and iteration-speed tradeoffs

Been operating at the edge of AI-first development for some time

Learned practical lessons from decades of enterprise-grade engineering patterns

Strong opinions on how old systems should be improved or replaced

High ownership and comfort working across many domains